An image sharpness metric for image processing applications using feedback

Eric P. Lam; Christopher A. Leddy; Stephen R. Nash

doi:10.1117/12.719083

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30 April 2007 An image sharpness metric for image processing applications using feedback

Eric P. Lam, Christopher A. Leddy, Stephen R. Nash

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Proceedings Volume 6543, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XVIII; 65430I (2007) https://doi.org/10.1117/12.719083
Event: Defense and Security Symposium, 2007, Orlando, Florida, United States

Abstract

Some image processing applications require an image to meet a quality metric before performing processing on it. If an image is too degraded such that it is difficult or impossible to reconstruct, the input image may be discarded. When conditions do not exhibit time-invariant image degradations, it is necessary to determine how sharp an image is. In this paper, we present a metric that measures the relative sharpness with respect to a reference image frame. The reference image frame may be a previous input image or even an output frame from the image processor. The sharpness metric is based on analyzing edges. The assumption of this problem is that input images are similar to each other in terms of observation angle and time. Although the input images are similar, it cannot be assumed that all input images are the same, because they are collected at different time samples.

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Eric P. Lam, Christopher A. Leddy, and Stephen R. Nash "An image sharpness metric for image processing applications using feedback", Proc. SPIE 6543, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XVIII, 65430I (30 April 2007); https://doi.org/10.1117/12.719083

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